Automatic extraction of offshore platforms using time-series Landsat-8 Operational Land Imager data
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- 作者：Yongxue Liua ; b ; d ; yongxue@nju.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Chao Suna ; b ; 1 ; sunchaozhuoyue@sohu.com" class="auth_mail" title="E-mail the corresponding author ; Yuhao Yanga ; 1 ; yangyuhaonju@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Minxi Zhoua ; 1 ; zhouminxi_103@hotmail.com" class="auth_mail" title="E-mail the corresponding author ; Wenfeng Zhanc ; 1 ; zhanwenfeng@nju.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Wangyu Chenga ; 1 ; chengwangyu.smile@163.com" class="auth_mail" title="E-mail the corresponding author
- 关键词：Offshore platforms ; Operational Land Imager ; Automation ; Time-series imagery ; Multi-refinement strategy
- 刊名：Remote Sensing of Environment
- 出版年：2016
- 出版时间：15 March 2016
- 年：2016
- 卷：175
- 期：Complete
- 页码：73-91
- 全文大小：6774 K
文摘
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An automatic method for extracting offshore platforms (AMEOP) was proposed.
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Two strategies (time-series and multi-refinement) were designed in the AMEOP.
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Three features (contextual, position- and size-invariance features) were incorporated.
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The AMEOP was well applied to the Gulfs of Thailand, Persian, and northern Mexico.
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The AMEOP was quantitatively assessed as objective, robust, and cost-effective.